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Human Cognitive Emulation

By Lee Rumpf. Human Cognitive Emulation. Abstract and Background.

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Human Cognitive Emulation

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  1. By Lee Rumpf Human Cognitive Emulation

  2. Abstract and Background Attempting to recreate accurate human responses to stimuli is something that man has been working on since the dawn of computers. While doing so would require a lifetime of research and work, bits and pieces can be attempted by individuals. Using a survey format, this experiment hopes to produce a unique response to a stimuli based on information gained about the user. While alone, the ramification of this lab can perhaps draw broad conclusions about groups of people and how they respond, combined with other techniques of emulating human thought patterns, computers can become closer and closer to accurately representing a real human This lab is designed to take in specific information from multiple users and eventually produce typecast that users can be put under. Using the typecast, a response to stimuli will be produced that hopefully matches what the user would do in real life.

  3. Construction def main(): answers = open('answers.txt', 'r') array = [] array = answers.read().split("\n") prompt = raw_input("new or name: ") if prompt == "new": prompt = raw_input("name: ") outfile = open(prompt, 'w') outfile.write(prompt+"\n") else: outfile = open(prompt, 'w') outfile.write(prompt+"\n") test = ["france","balls","home","salad","poodle","oar","classic rock","mary","door","math"] count = 0 hard = dict(zip(test, [None]*len(test))) for a in test: count = count + 1 for k in range(len(array)-1): temp = array[k].split(',') ans = temp[count] hard[a][k] = [ans] answers.close() The program is written in Python and as of now designed to survey the user for a response to the stimuli. Current work includes designing a method of storing data over time in a manner allowing it to be restored and edited. mySQL my provide to be the solution to that problem.

  4. Results and Conclusion rrumpf@othello:~/comsys/project$ python reader.py file name: will will france - team america balls - gold bond home - is where the heart is salad - dressing poodle - france oar - ty otto classic rock - acdc mary - had a little lamb door - frame math - test Currently, the program survey.py creates a survey that the user completes and then saves it to a file named after the user. A reader.py program prompts for the user name to retrieve their information in a read-only. The optimal results would be to put each person in his or her own typecast, with similarities to and differences with other users. Then when a stimulus is given to the "computer" user the response will match, within a certain error bound, the reaction the user would give. More likely the user will be put with a group of other users who share similar traits with the user. Then the program will analyze the responses of all the users in the group and determine a response to a given stimuli. Chances are that this result will be less accurate, but more feasible.

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